A recursive feature eliminating method based on a support vector machine (SVM-RFE) is widely used in data intensive applications, such as disease genes selection, structured data mining, and unstructured data mining, etc. The SVM-RFE method may comprise: SVM training an input training data to classify the training data, wherein the training data may comprise a plurality of training samples corresponding to a group of features and class labels associated with each of the training samples; eliminating at least one feature with a minimum ranking criterion from the group of features; and repeating the aforementioned SVM training and eliminating until the group becomes empty. The SVM-RFE may be used to rank the features, for example, to rank the genes that may cause a disease. Rounds of SVM training and eliminating are independent with each other.